Hypoinsulinaemic, hypoketotic hypoglycaemia due to mosaic genetic activation of PI3-kinase
Bibliographic record
Abstract
Objective Genetic activation of the insulin signal-transducing kinase AKT2 causes syndromic hypoketotic hypoglycaemia without elevated insulin. Mosaic activating mutations in class 1A phospatidylinositol-3-kinase (PI3K), upstream from AKT2 in insulin signalling, are known to cause segmental overgrowth, but the metabolic consequences have not been systematically reported. We assess the metabolic phenotype of 22 patients with mosaic activating mutations affecting PI3K, thereby providing new insight into the metabolic function of this complex node in insulin signal transduction. Methods Three patients with megalencephaly, diffuse asymmetric overgrowth, hypoketotic, hypoinsulinaemic hypoglycaemia and no AKT2 mutation underwent further genetic, clinical and metabolic investigation. Signalling in dermal fibroblasts from one patient and efficacy of the mTOR inhibitor Sirolimus on pathway activation were examined. Finally, the metabolic profile of a cohort of 19 further patients with mosaic activating mutations in PI3K was assessed. Results In the first three patients, mosaic mutations in PIK3CA (p.Gly118Asp or p.Glu726Lys) or PIK3R2 (p.Gly373Arg) were found. In different tissue samples available from one patient, the PIK3CA p.Glu726Lys mutation was present at burdens from 24% to 42%, with the highest level in the liver. Dermal fibroblasts showed increased basal AKT phosphorylation which was potently suppressed by Sirolimus. Nineteen further patients with mosaic mutations in PIK3CA had neither clinical nor biochemical evidence of hypoglycaemia. Conclusions Mosaic mutations activating class 1A PI3K cause severe non-ketotic hypoglycaemia in a subset of patients, with the metabolic phenotype presumably related to the extent of mosaicism within the liver. mTOR or PI3K inhibitors offer the prospect for future therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".